| Metric | Value |
|---|---|
| ELPD | -3.70 |
| ELPD_SE | 6.21 |
| LOOIC | 7.41 |
| LOOIC_SE | 12.42 |
| WAIC | 7.33 |
| R2 | 0.00 |
| R2 (adj.) | -0.01 |
| RMSE | 0.25 |
| Sigma | 0.25 |
For interpretation of performance metrics, please refer to this documentation.
Error in ans[ypos] <- rep(yes, length.out = len)[ypos]: replacement has length zero
| Parameter | Median | 95% CI | pd | Rhat | ESS | Prior |
|---|---|---|---|---|---|---|
| (Intercept) | 0.02 | (-0.05, 0.10) | 72.88% | 1.000 | 2757.00 | Normal (0.02 +- 0.63) |
To find out more about table summary options, please refer to this documentation.
Error in if (nrow * ncol < n) {: missing value where TRUE/FALSE needed
We fitted a constant (intercept-only) Bayesian linear model (estimated using MCMC sampling with 4 chains of 2000 iterations and a warmup of 1000) to predict loneliness_delta1 (formula: loneliness_delta1 ~ 1). . The model’s intercept is at 0.02 (95% CI (-0.05, 0.10)).
Following the Sequential Effect eXistence and sIgnificance Testing (SEXIT) framework, we report the median of the posterior distribution and its 95% CI (Highest Density Interval), along the probability of direction (pd), the probability of significance and the probability of being large. The thresholds beyond which the effect is considered as significant (i.e., non-negligible) and large are |0.01| and |0.08| (corresponding respectively to 0.05 and 0.30 of the outcome’s SD). Convergence and stability of the Bayesian sampling has been assessed using R-hat, which should be below 1.01 (Vehtari et al., 2019), and Effective Sample Size (ESS), which should be greater than 1000 (Burkner, 2017).
---
title: "Regression model summary from `{easystats}`"
output:
flexdashboard::flex_dashboard:
theme:
version: 4
# bg: "#101010"
# fg: "#FDF7F7"
primary: "#0054AD"
base_font:
google: Prompt
code_font:
google: JetBrains Mono
params:
model: model
check_model_args: check_model_args
parameters_args: parameters_args
performance_args: performance_args
---
```{r setup, include=FALSE}
library(flexdashboard)
library(easystats)
# Since not all regression model are supported across all packages, make the
# dashboard chunks more fault-tolerant. E.g. a model might be supported in
# `{parameters}`, but not in `{report}`.
#
# For this reason, `error = TRUE`
knitr::opts_chunk$set(
error = TRUE,
out.width = "100%"
)
# helper function for printing `{report}` outputs
bracket_to_parantheses <- function(text) {
gsub("]", ")", gsub("[", "(", text, fixed = TRUE), fixed = TRUE)
}
```
```{r easydashboard-1}
# Get user-specified model data
model <- params$model
# Is it supported by `{easystats}`? Skip evaluation of the following chunks if not.
is_supported <- insight::is_model_supported(model)
if (!is_supported) {
unsupported_message <- sprintf(
"Unfortunately, objects of class `%s` are not yet supported in {easystats}.\n
For a list of supported models, see `insight::supported_models()`.",
class(model)[1]
)
}
```
Model fit
=====================================
Column {data-width=700}
-----------------------------------------------------------------------
### Assumption checks
```{r check-model, eval=is_supported, fig.height=10, fig.width=10}
check_model_args <- c(list(model), params$check_model_args)
# add verbose, if not done yet
if (is.null(check_model_args$verbose)) check_model_args$verbose <- FALSE
tryCatch(
{
do.call(performance::check_model, check_model_args)
},
error = function(e) {
cat(insight::format_message(
"\nSomething did not work as expected. Please file an issue at {.url https://github.com/easystats/easystats/issues/} and post the following output:",
paste0("\n`", e$message, "`")
))
}
)
```
```{r easydashboard-2, eval=!is_supported}
cat(unsupported_message)
```
Column {data-width=300}
-----------------------------------------------------------------------
### Indices of model fit
```{r easydashboard-3, eval=is_supported}
# {performance}
performance_args <- c(list(model), params$performance_args)
# add verbose, if not done yet
if (is.null(performance_args$verbose)) performance_args$verbose <- FALSE
table_performance <- do.call(performance::performance, performance_args)
print_md(table_performance, layout = "vertical", caption = NULL)
```
```{r easydashboard-4, eval=!is_supported}
cat(unsupported_message)
```
For interpretation of performance metrics, please refer to <a href="https://easystats.github.io/performance/reference/model_performance.html" target="_blank">this documentation</a>.
Parameter estimates
=====================================
Column {data-width=550}
-----------------------------------------------------------------------
### Plot
```{r dot-whisker, eval=is_supported}
# `{parameters}`
parameters_args <- c(list(model), params$parameters_args)
# add verbose, if not done yet
if (is.null(parameters_args$verbose)) parameters_args$verbose <- FALSE
table_parameters <- do.call(parameters::parameters, parameters_args)
plot(table_parameters)
```
```{r easydashboard-5, eval=!is_supported}
cat(unsupported_message)
```
Column {data-width=450}
-----------------------------------------------------------------------
### Tabular summary
```{r easydashboard-6, eval=is_supported}
print_md(table_parameters, caption = NULL)
```
```{r easydashboard-7, eval=!is_supported}
cat(unsupported_message)
```
To find out more about table summary options, please refer to <a href="https://easystats.github.io/parameters/reference/model_parameters.html" target="_blank">this documentation</a>.
Predicted Values
=====================================
Column {data-width=600}
-----------------------------------------------------------------------
### Plot
```{r expected-values, eval=is_supported, fig.height=10, fig.width=10}
# {modelbased}
int_terms <- find_interactions(model, component = "conditional", flatten = TRUE)
con_terms <- find_variables(model)$conditional
if (is.null(int_terms)) {
model_terms <- con_terms
} else {
model_terms <- clean_names(int_terms)
int_terms <- unique(unlist(strsplit(clean_names(int_terms), ":", fixed = TRUE)))
model_terms <- c(model_terms, setdiff(con_terms, int_terms))
}
# check some exceptions here: logistic regression models with factor response
# usually require the response to be included in the model, else `get_modelmatrix()`
# fails, which is required to compute SE/CI for `get_predicted()`
response <- find_response(model)
minfo <- model_info(model)
model_data <- get_data(model)
include_response <- minfo$is_binomial && minfo$is_logit && is.factor(model_data[[response]])
text_modelbased <- tryCatch(
{
lapply(unique(model_terms), function(i) {
estimate_means(model, by = i, verbose = FALSE)
})
},
error = function(e) {
cat(insight::format_message(
"\nSomething did not work as expected. Please file an issue at {.url https://github.com/easystats/easystats/issues/} and post the following output:",
paste0("\n`", e$message, "`")
))
NULL
}
)
if (!is.null(text_modelbased)) {
ggplot2::theme_set(theme_modern())
# all_plots <- lapply(text_modelbased, function(i) {
# out <- do.call(visualisation_recipe, c(list(i), modelbased_args))
# plot(out) + ggplot2::ggtitle("")
# })
all_plots <- lapply(text_modelbased, function(i) {
out <- visualisation_recipe(i, show_data = FALSE)
plot(out) + ggplot2::ggtitle("")
})
see::plots(all_plots, n_columns = round(sqrt(length(text_modelbased))))
}
```
```{r easydashboard-8, eval=!is_supported}
cat(unsupported_message)
```
Column {data-width=400}
-----------------------------------------------------------------------
### Tabular summary
```{r easydashboard-9, eval=is_supported, results="asis"}
if (!is.null(text_modelbased)) {
for (i in text_modelbased) {
tmp <- print_md(i)
tmp[length(tmp)] <- paste(insight::compact_character(strsplit(tmp[length(tmp)], "\n")[[1]]), collapse = "; ")
print(tmp)
}
}
```
```{r easydashboard-10, eval=!is_supported}
cat(unsupported_message)
```
Text reports
=====================================
Column {data-width=500}
-----------------------------------------------------------------------
### Textual summary
```{r easydashboard-11, eval=is_supported, results='asis', collapse=TRUE}
# {report}
text_report <- tryCatch(
{
report(model, verbose = FALSE)
},
error = function(e) {
cat(insight::format_message(
"\nSomething did not work as expected. Please file an issue at {.url https://github.com/easystats/easystats/issues/} and post the following output:",
paste0("\n`", e$message, "`")
))
NULL
}
)
text_report_performance <- tryCatch(
{
report_performance(model, verbose = FALSE)
},
error = function(e) {
cat(insight::format_message(
"\nSomething did not work as expected. Please file an issue at {.url https://github.com/easystats/easystats/issues/} and post the following output:",
paste0("\n`", e$message, "`")
))
NULL
}
)
if (!is.null(text_report)) {
cat(bracket_to_parantheses(text_report))
cat("\n")
}
if (!is.null(text_report_performance)) {
cat(bracket_to_parantheses(text_report_performance))
}
```
```{r easydashboard-12, eval=!is_supported}
cat(unsupported_message)
```
Column {data-width=500}
-----------------------------------------------------------------------
### Model information
```{r easydashboard-13, eval=is_supported}
model_info_data <- insight::model_info(model, verbose = FALSE)
model_info_data <- datawizard::data_to_long(as.data.frame(insight::compact_list(model_info_data)))
DT::datatable(model_info_data)
```
```{r easydashboard-14, eval=!is_supported}
cat(unsupported_message)
```